UAV Power Line Inspection Path Planning With Real-Time Wire Detection
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Solution Overview
Problem
Current electric power inspection methods using unmanned aerial vehicles (UAVs) face challenges in efficiently navigating around obstacles and detecting thin wires, particularly in automatic flight modes that rely on pre-collected RTK data, which can be outdated and fail to account for new obstacles, posing safety risks and efficiency issues.
Innovation Solution
The method involves using a point cloud sensor on the UAV to obtain target parameters such as distance and extension direction of electric wires, determining a flight path based on these parameters, and controlling the UAV to perform operations while avoiding obstacles, utilizing sensors like lidar, cameras, or millimeter wave radar for real-time data acquisition and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic flight operation mode using pre-collected RTK data is used, then flight automation is improved, but safety deteriorates due to new obstacles appearing on the flight trajectory
Solution Approach 1:
The patent transitions from static pre-collected RTK trajectory data to dynamic real-time obstacle detection and avoidance. The UAV continuously acquires obstacle information during flight and dynamically adjusts its trajectory, making the flight path adaptive to changing environmental conditions while maintaining automated operation.
Solution Approach 2:
The patent performs preliminary obstacle detection and classification before final flight path determination. The system pre-processes sensor data to identify and classify obstacles, then uses this information to plan safe flight paths in advance, combining proactive detection with real-time response.
2Reliability
If manual flight operation mode is used, then flight safety is improved through operator control, but inspection efficiency deteriorates due to higher requirements for the flyer
Solution Approach 1:
The patent enables the UAV to perform self-service through automated obstacle detection, classification, and avoidance functions. The system independently processes sensor data, identifies obstacles, and adjusts flight paths without human intervention, eliminating the need for highly skilled manual operators while maintaining safety and improving efficiency.
Solution Approach 2:
The patent replaces manual mechanical control with automated sensor-based detection and control systems. Optical sensors, ultrasonic sensors, and other detection devices substitute for human visual and manual control, enabling automated safe flight operations.
3Ease of operation
If visual detection methods are used for wire detection, then ease of operation is improved, but measurement precision deteriorates due to difficulty in detecting thin wires
Solution Approach 1:
The patent merges multiple detection methods including optical sensors, ultrasonic sensors, and point cloud processing to detect thin wires. By combining these different sensing modalities, the system overcomes the limitations of single visual detection methods and achieves high precision wire detection while maintaining ease of automated operation.
Solution Approach 2:
The patent introduces point cloud processing as an intermediary between raw sensor data and wire detection. The point cloud technology serves as a mediator that enhances the detection capability for thin wires by creating detailed three-dimensional representations, improving measurement precision without complicating the overall detection process.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the safety and efficiency of electric power inspection by allowing the UAV to detect and avoid obstacles in real-time, including thin wires, and ensures automated operation with improved anti-jamming capabilities, compared to traditional methods that struggle with visual detection and pre-collected data.
Implementation Method 1
the point cloud sensor comprises at least one of the following: a lidar
Implementation Method 2
the point cloud sensor comprises at least one of the following: a millimeter wave radar, a rotating millimeter wave radar, or an ultrasonic radar
Data Source
AI summary
An operating method of an aerial vehicle may comprise obtaining target parameters, the target parameters being acquired by an on-board sensor of the aerial vehicle during movement of the aerial vehicle, the target parameters comprising a distance between the aerial vehicle and a target object and an extension direction of the target object; determining a flight path of the aerial vehicle based on the target parameters; and controlling the aerial vehicle to perform an operation based on the flight path of the aerial vehicle.